期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2007
卷号：XXXVI-5/C55
出版社：Copernicus Publications
摘要：The recently growing interest the autonomous vehicle navigation has directed a lot of attention to technologies that are capable of mapping the environment around a moving vehicle in real-time. The two past Grand Challenges and the upcoming Urban Challenge, organized by the US Defense Advanced Research Projects Agency (DARPA), created not only a lot of interest in robotics, but resulted in major developments in the past few years, including the capability for effective real-time mapping of the vicinity of the robots. Autonomous vehicle navigation is primarily based on waypoint navigation, but to stay on track and avoid obstacles the vehicles must have sophisticated sensor sy stems. In particular, this is the case in urban environments, where the robots deal with a number of moving vehicles. From a conceptual perspective, the required sensing capability of an autonomous vehicle is comparable to that of a mobile mapping system, and the major difference is the real-time processing of the raw sensory data into high-level object space information. This paper will review the recent developments in real-time mobile mapping, and will provide an analysis of the real-time mapping effort through the experiences of the OSU DARPA Ground Challenge group that raced as the TerraMax team in 2004 and Buckeye Deserts in 2005
